MATLAB and Simulink Robotics Arena

Learn how you can use MATLAB® and Simulink® to design robots and unmanned vehicles for student competitions. MathWorks experts share their knowledge of topics such as perception and control algorithm design, modeling and simulation, software and hardware implementation, and data analysis. This video series will also feature student teams that have successfully used MATLAB and Simulink in their competitions.

Introduction to Robotic Systems
Meet MATLAB and Simulink Robotics Arena team members Sebastian Castro and Connell D’Souza as they discuss designing a robotic system and the support provided to robotics student competition teams.

Introduction to Contact Modeling, Part 1
Sebastian Castro and Ed Marquez Brunal introduce the fundamentals of mechanical contact modeling and simulation with Simulink, as well as show examples for automotive and robotics applications.

Direction of Arrival with MATLAB
Stephen Cronin from the Robotics Association at Embry-Riddle Aeronautical University demonstrates how to detect the direction of arrival of an underwater acoustic signal using MATLAB.

Walking Robots, Part 2: Actuation and Control
Join Sebastian Castro as he shows you how you can use Simulink and the Simscape product family to connect a walking robot model to detailed actuator models with motion planning and control algorithms.

Real-Time Beat Tracking Challenge
Jeremy Bell, Angus Keatinge, and James Wagner of The University of New South Wales (UNSW Sydney) discuss their team’s winning entry to the IEEE Signal Processing Cup 2017.

Deploying Algorithms to ROS
Join Sebastian Castro and Pulkit Kapur as they show how automatic code generation tools can help you deploy algorithms developed in MATLAB and Simulink to run in the Robot Operating System (ROS).

Building Interactive Design Tools
Build interactive design tools to reduce development time. Zachary Leitzau from Embry-Riddle Aeronautical University demonstrates the use of a self-built app to help design a model airplane.

Simulating Quadcopter Missions
Simulation is a great way to test and tune control algorithms for quadcopters. Julien Cassette talks about using Simulink, Robotics Operating System (ROS), and Gazebo to simulate quadcopter missions from student competitions.

Optimizing Airframe Sizing
Follow Joshua Williams from Cornell University Unmanned Air Systems (CUAir) as he demonstrates the use of a genetic algorithm to optimize airframe sizing for model airplanes.

Designing Distributed Systems with ROS
Join Sebastian Castro and Connell D’Souza as they discuss techniques in Simulink to design and deploy multirate and multiplatform robotics algorithms with the Robot Operating System (ROS).

Designing Robot Manipulator Algorithms
Accelerate the design of robot manipulator algorithms by using the Robotics Systems Toolbox functionality and integrating robot models with simulation tools to program and test manipulation tasks.

Introduction to Filter Design
Join Mark Schwab and Connell D'Souza as they demonstrate the use of the Filter Designer app and interactively design filters for digital signal processing that can be implemented in MATLAB or Simulink.

From Data to Model
Create a model for a piece of hardware from input and output data using the System Identification app. Connell D'Souza and Kris Fedorenko explain the workflow from data gathering to model evaluation.

Deep Learning with NVIDIA Jetson and ROS
Learn how GPU Coder can be used to deploy deep learning algorithms from MATLAB to embedded NVIDIA GPUs, and how the deployed code can be used with the Robot Operating System (ROS).

Ball Tracking with a Desktop Computer
In this session you’ll learn how to deploy MATLAB® and Simulink® onto a desktop computer for the purpose of controlling an Unmanned Vehicle System in student competitions.